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Biopharma & Investing
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Alexion is kicking butt. Being this good is almost boring.

Gilead, both Johns are stepping down. Running a big pharma and being that good is boring too, I guess.

Keytruda approved in China. Big problem for Beigene.

BAN2401 is not a viable drug. It does not work. No way, no how. I think people who write about biotech for a living should write less quickly (and less from a company script) and read some textbooks on statistics, medicine and pharmacology. Friends email me news here and I was aghast to see nearly every biotech ‘observer’ pathetically record that BANB2401 produced a promising result. “Stat” (whatever that is), CNBC (predictable), Endpoints (this is that weird guy’s blog), etc. All the usual suspects just don’t know how to read clinical data. Why even try to chronicle the history of an industry if you just don’t get it? Maybe wait until the dust settles before writing an embarassing headline. It is really emblematic of an epidemic: media companies don’t have big budgets, so they hire whoever they can to write whatever they want on a field they don’t comprehend. I saw some financial journalists completely fail to comprehend amortization recently. A silent smile is all I can produce. So, I understand predicting the future is too tough for biotech writers, but at least chronicle the past correctly.

Anyway, the stock market promptly reacted to the BANB2401 data for the failure that it was. Antibodies don’t enter the brain, let alone the cortical areas, the parenchyma, etc. It’s fucking physics. F=MA? Tight junctions? Next, we saw what happens when a-beta antibodies are dosed in AD: bapi, sola, etc. Finally, THIS data is a piece of work. Don’t trust any p>0.01. That is the same as p>0.05. For Christ’s sake, don’t trust data at p>0.01. Drugs don’t work by chance, ever. At least drugs I care about. Next, the idea that one drug dose worked and one didn’t is humorous. Unless you have a clear explanation as to why one dose wouldn’t work and one would, you have to group and average the cohorts. The company wouldn’t waste precious power and resources if they thought there would be no activity in the dose cohort. Most antibodies stick around. It’s plausible that more frequent dosing would do the trick, but unlikely. Same thing with timing of therapeutic effect: the separation that occurs at 18 months has no trace at 12 months. Is there a plausible reason for that? Sure but I’d be more convinced if it persisted at 24 months. Very, very few drugs have a 12 month delayed therapeutic onset. FInally, this isn’t a clinically meaningful result (hence the p=0.016 or whatever it was). ADAS-COG is a 70 point scale. A 2 point improvement is exactly what these antibodies were invented to NOT produce. I’ve wasted enough transistor state changes writing this. I’m sorry, electrons.

Book Review – How Not to Be Wrong: The Power of Mathematical Thinking – Jordan Ellenberg
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It’s hard for me to review a book like HNTBW. One lens to look at it through is, “could I have done better”? I’ll go through areas I think were lacking, but this is a paean to math that deserves your attention. Of course, One of Bill Gates’s “10 Favorite Books”, which I’m sure is a subset of a larger list of his favored reads, which is apparently, everything he reads.
The title of this book could not have been written by its author. It is largely meaningless. The title should have been: “My random thoughts on Math and Statistics which will hopefully get you interested in Math”. There is no theme that I could discern other than the author’s obsession with math history. So Ellenberg’s structural organization is very poor. He meanders from topic to topic, staying far too long on some (statistics), ignoring others completely. On the plus side, he is imaginative with references to F Scott Fitzgerald, the erstwhile mathematician Wallace (David Foster!) and various other compelling orthogonals. His actual writing style is excellent. Clearly a keen mind, he restrains himself from overpowering the reader with the standard philosophical/mathematical overwrought vocabulary. “He’s just an average joe math professor!” is the feeling you get and it keeps you engaged.
Ellenberg tries to do a good deed. His message is that this book will somehow help you think more structurally. It won’t do so, directly. There are very few (maybe two?) proofs in the book and other than a brief explanation of reductio ad absurdum, very few logical techniques are actually employed. Despite that, Ellenberg tackles hundreds of problems with a sneaky mathematical armamentarium. I fear his secret spies could have been more direct: on battalion, a little more actual math wouldn’t have scared the reader and empowered the work. Some of HNTBW feels like a parlor trick, with the reader forced to trust Ellenberg that “there’s math in here, don’t worry! I’m not going to show it to you, but it’s there!”.
Understandably HNTBW has a strong focus on statistics but here Ellenberg makes a very poor showing. In the classic example of multiplicity errors gone haywire, Ellenberg introduces the GWAS experiments that yours truly reviews on a daily basis but doesn’t describe p-value correction. This and other glaring omissions, like any discussion of why people insist on making post-hoc observations that fail to repeat themselves, could have served readers well.
The second half of the book is a more poetic journey through math history. While he is no Newman and this is no anthology, Ellenberg’s near lyricism is enchanting and awe-inspiring. The last chapter in the book is a monument to humility, creativity and achievement in maths. Still, HNTBW is not Godel-Escher-Bach, nor does it try to be. Ellenberg just teases us with math, often namedropping greats and taking us on a tour meant to enthrall us and learn more. A much-needed manual on how to actually think in a structurally correct way was a titular trick I’m happy I fell for. I highly recommend this book. 9/10.

Glossary – Dedicated to various journalists at Bloomberg, CNBC, Stat, etc. who I wouldn’t hire to change my cat litter because they apparently are unaware of the following:
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a priori – generally used as a synonym for “pre-specified” in statistics.
alpha – the likelihood of making a type I error, or rejecting the null hypothesis when it is true
beta – the likelihood of making a type II error, or incorrectly concluding the null hypothesis is correct
clinical significance – as opposed to statistical significance, the degree to which a medicine is clinically relevant to a patient. 2 points on a 70 point scale, for instance, is not clinically relevant.
co-primary endpoint – if you split alpha a priori, you can examine two endpoints at once. however, both endpoints must be met with the reduced alpha to infer the rejection of ANY null hypothesis.
deductive reasoning – using the rules of logic to form inferences with certain conclusions.
Fisher, Sir Ronald – British statistician who was the father of statistics. Probably the first person you could call a statistician.
Fisher’s Exact Test – A personal favorite, a categorical statistical test for contingency tables.
Gauss, Carl Friedrich – Mathematical deity who the normal distribution is named after
inductive reasoning – find patterns in empirical data. any inference where the premise is giving us some evidence of truth, resulting in a probabilistic inference
inference – something many, many liberal arts majors are incapable of
mechanistic plausibility – The plausibility of an investigational drug’s mechanism of action. Similar drugs having failed to elicit a beneficial response in a similar patient population would impinge negatively on plausibility.
null hypothesis – the hypothesis we seek to invalidate with an experiment, a reductio ad absurdum technique
Pearson, Karl – another father of statistics, see Pearson’s chi-squared test.
p-value – the quantification of statistical significance, where the p-value must be less than alpha.
pre-specified endpoint – Typically, a between-group comparison using a statistical method that is articulated in the SAP prior to trial initiation.
primary endpoint – The ONE a priori statistical test hypothesized in the SAP. A clinical trial can only interrogate ONE hypothesis so as to avoid unduly respecting post hoc observations. IF the primary endpoint is met with statistical significance, a secondary endpoint may be evaluated as per the SAP with the same alpha level as the primary endpoint (no alpha is considered spent). Dose-ranging studies make pre-specified endpoints extremely hard to meet given the limited power of making each dose a co-primary endpoint. One may group all or some doses and retain full alpha, but one may not assign full alpha (0.05) for all doses. If 5 doses are being interrogated, the alpha must be SPLIT between these doses (roughly 0.01 each).
post hoc analysis – An after-the-fact analysis of data which is hypothesis-generating ONLY. Typically used by companies and characters of ill repute to bolster clinical trials which have failed to reach statistical significance. “Shooting an arrow and painting the bullseye after”.
power: 1 – beta
probability distribution: a description of probability of all possible outcomes in an experiment
statistical analysis plan (SAP) – the statistical protocol for a clinical trial
statistical significance – when p < alpha, the probability that the results obtained if the null hypothesis is true, were due to chance
type I error: rejecting a true null-hypothesis
type II error: failure to reject a false null hypothesis

Spend more time reading books and less time giving out an unearned opinion. I doubt many “communications” majors (or most other liberal arts majors) are intelligent enough (yes, I am going there) to have done well in mathematics and statistics. As Dalio says, ask yourself if you’ve earned the right to have an opinion. You should not opine on biopharmaceuticals unless the above is facile and simple to you. Statistics is the lens with which we see the modern data-driven world. Go back to school and actually learn something, if you have to. The above are trivially basic–we don’t go into Bayes vs frequentist, ANOVA, actual math of a statistical test, stratification methods, parameterization, multiplicity correction techniques, LOCF/BOCF and missing data and other still simple topics.

I like Global Blood Therapies’ (GBT) drug. I’m still not through with my work but I suspect this is a real disease-modifying drug that treats the underlying cause of sickle cell anemia. A real breakthrough. This company may become as large as an Alexion or Onyx (pre-takeover) in due time.

CAR-T looks like a commercial dud. Sorry, Celgene and Gilead. Those billions are unlikely to come back. Who knows, though. Antibodies had slow uptake at first. What I’ve heard from various sources is institutions don’t want to do CAR-T. The side effects are tough and the reimbursement is difficult. This is good for companies like Morphosys and Seattle Genetics who are using traditional antibodies for CAR-T targets and some are seeing good results. Bad news for the 200 private CAR-Ts, ADAP, CLLS and everyone else who wants to be JUNO and KITE.

The flu market is heating up with new drugs from Roche, Shionogi and Vertex and some promise of a universal vaccine.

Idorsia is chugging along with their rHTN (resistant hypertension) ERA (endothelin receptor antagonist). Guess who also bought an ERA way back when 😉

Starting to watch the vaccine space very closely. One of the few areas of pharmaceuticals that is truly cost-effective, hard to replicate/genericize, etc. Every new vaccine company seems to get acquired (IDBE, CRXL for you old timers).

Papers I’ve Read
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I’ve been reading some proprietary materials, so excuse the lack of commentary.

GBT440 increases haemoglobin oxygen affinity, reduces sickling and prolongs RBC half-life in a murine model of sickle cell disease. Oksenberg et al. Br J Haematology 2016.
Tremendous work from the GBT team here. This panel of preclinical data is comprehensive. Almost every question I would have asked is asked and answered here. The murine transgenic model was a bit of a flop, which was interesting. Nevertheless, GBT440 certainly works as advertised, increasing Hb-O2 affinity, thereby raising the question of whether these HbS-GBT440 complexes are TOO oxygen-hungry and will never release this oxygen to tissues. It would still (or should still) stop polymerization of the aggregation-prone HbS species. One question I would have answered is trying to determine binding kinetics here, especially Koff. Km wouldn’t hurt, we see some EC50s in the micro molar range. The engineering of a compound devoid of plasma binding is somewhat surprising. If I had to decide on buying this whole company, I’d probably run that assay independently to be really sure as it is not often compounds have close to zero albumin affinity.

New Developments in Anti-Sickling Agents: Can Drugs Directly Prevent the Polymerization of Sickle Haemoglobin in Vivo? Oder, et al. Br J Haematol 2016.
Decent review. Somewhat stunning that there are 20T (trillion!) red blood cells, which are most of your cells (!!!). Each RBC has 250 million (!) hemoglobin proteins. so that is … 2*10^13 X 2.5*10^8 = 5.0*10^21. You need 20% of that hemoglobin ‘fixed’ according to various in vitro studies, so 1.0*10^21. The MW of GBT440 is 337, so the weight of the drug you need is 3.37*10^23. Avogadro’s # is 6.022*10^23. So you need 500mg of GBT440, but the bioavailability of the drug is something like 50%, so you need 1g/day. That’s roughly what they dosed in Phase 3. Incredible!

Personal
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I received a rather ineluctable haircut after “looking like Harry Potter” (at least to various other convicts) for far too long. One barber agreed to “give me the Brad Pitt” after discussing various style options. Consequently, I have very little hair left. No longer hirsute, life goes on! Just like the memes, barbers here also insist on reciting “say no more, fam” prior to destroying your appearance.

Why does Bill Gates review EVERY trash book and think they’re good? Poor guy. Bridge & reading psychosocial commentary is one helluva retirement. At least his healthcare stuff seems well done. I’ll probably learn how to play bridge soon.

Biopharma & Investing
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–I left off musing about the inability for public equities to achieve a meaningful risk-adjusted positive return. This is an unorthodox and uncomfortable opinion I have tremendous conviction in. The impact of some of my opinion is derived from explaining the post hoc ergo propter hoc fallacy: folks who disagree with me point to historical returns instead of the underlying structure for what to expect from the future. History is not a guide for the future here, even 100 years of history. The US will never be in the same situation it was then, ever again (scale, globalism). Or there is a framing error: they are looking at US equities only, forgetting there are some failed states that want their stock markets back. I’m sure the Soviets and Japanese thought THEIR stock markets would always go up, too. Aren’t we all lucky to have been born here? Boris Buffetski and Waryu Buffetashi are missing in action. I’ll have more to say, not only on why historical returns for global equities are not that impressive on a real- and tax-adjusted basis, but also why structural flaws will limit future equity returns to very close to zero, if at all positive.

–Still working on the time-consuming Merck analysis. I’ve figured out the classification of all their drugs over the years. However, the vaccines are tricky given some of them have been refreshed for 50+ years! We’ll exclude the vaccine business for our purposes and adjust the R&D a bit. Still, huge hits like Fosamax, Singulair, Januvia and Zocor promise that Merck’s been far more productive than Pfizer. We’ll see what the final calculations say soon.

–Wealth can’t be understood without age-adjusting. Anyone who has read ‘Snowball’ or spent a lot of time thinking about compounding understands this. Getting a good head start is nice, but keeping pace is difficult. I’m going to make a chart of wealth on an age-adjusted and inflation-adjusted basis and run IRR calculations comparing individual wealth as you would corporate. Here’s the work on Buffett:

From 1958 to today, Buffett compounded his personal wealth by about 21.5%, from $1 million to $82 billion. I will try to undo some of his donations and see how he would have done by keeping all his BRK stock. I’m not sure what impact that’s had on his wealth.

At 30, Buffett’s $1 million of wealth is $8.5m in today’s money.
At 35 (my age), Buffett’s then $7 million of wealth would be $56m in today’s money. (So far so good for me!). From this age, Buffett compounded at 19.33%. That’s every year, for the next 53 years. Astounding!

At 43 (year is 1974), gaining steaming, Buffett’s $34m is worth $193m in today’s money. He compounds from 19% from here.

At 52, he’s worth $376 million, in today’s terms, $951 million. A billionaire. From here, he returns 16% per annum.

What’s amazing about WEB is we celebrate billionaires so much in today’s culture (except for CNBC, because they’re nazi socialist/communists), and he was a little late to the party. It shows you that wealth is about longevity and having the right mental framework for long-term success. Buffett whizzed past a lot of early birds with his consistency.

–Finally, a repeated thank you to the management team at Vyera who is delivering all this success for me. Would be nothing without you! Stunning R&D productivity with 4 INDs likely (3 already in the bag!) in just 3 years. May you keep compounding 🙂

Book Review – A Brief History of Time – Stephen Hawking
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Dr. Hawking recently passed away and so perhaps he has taken a throne next to Einstein, St. Augustine, Descartes, Pascal and others in a room God marks as “Nice Tries”. Explaining the universe is a tricky avocation. Having ALS at the same time would make one’s job harder. Nevertheless, Hawking made profound advances in theoretical physics and cosmology which he has been duly lauded for. Many pop science writers are unpublished hacks, but Hawking had the scientific chops to straddle both worlds. While his disability made him a celebrity, and one wonders if he would have been as popular without it, or if some researchers secretly resented him for it, we won’t know and shouldn’t care.
About the book!? Right! Well, “A Brief History” is one of the most printed books of all time. It’s that bestseller that everyone has on their bookshelf and no one has read cover to cover. As a preteen/early teen I was a particle physics enthusiast, obsessing over subatomic taxonomy and I STILL didn’t read ABHOT, partially because I felt Hawking was TOO celebrated and partially because of its pop orientation. However, I admit for the early part of this period, I was awed and inspired by this computer-voiced crippled man who could still level you with his mind. And in ABHOT, Hawking does just that.
ABHOT is very far from a textbook, and it is too simplistic and even patronizing in parts (Hawking refers to Kant’s seminal Critique of Pure Reason as “obscure”). However, in general, ABHOT is mostly too difficult to fully understand and appreciate. I challenge the lay person to keep attention during Chapter 8, for instance. “The Origin and Fate of the Universe” is an abstract mess that is hard to follow unless you have an undying curiosity about this field. If this is your first time encountering spin states, the cosmological constant, or even simple quantum mechanics, you will be lost trying to follow this work.
If understanding the universe is a tricky business, then perhaps explaining the universe is even more difficult. I don’t fault Hawking for sometimes deliberately leaving out crucial mathematical details. He goes on to say “well, I proved this” and “this theory requires that” but leaves the reader without evidence of his line of thinking, only his grand authority. I won’t cavil about the published refusing the words billion and trillion, instead relying on “6 million million million”, as if this is an easier concept to understand than scientific notation. Hawking annoyingly explains in parentheses how many zeroes the author is indicating. The book is too short to be useful–at less than 200 pages of the main text, some necessary core concepts are completely eliminated. We’re left with lots of questions about the nature of time, and perhaps that is the point. Hawking drills in over and over again that time is not linear in the sense that we understand it. It likely has no beginning, no end and no absolute measurement. He explains relativity and spacetime reasonably well but he doesn’t evoke the wonder you might expect in such a numinous subject. For the more mundane concepts, the reader will be bored. Do you really care what happened in the femtoseconds after the Big Bang? Hawking forgets his audience with excursions that can sometimes be painful.
Concepts like black holes and radiation they emit are again, far from terrestrial, even in his attempt to ground the subject matter. Advanced readers are simultaneously puzzled and frustrated by a lack of detail and all-too-frequent hand-waving and progression of a concept. A more detailed work would be even drier, and perhaps risk only 0.5% of purchasers reading the book than the current 1.0%. Still, if you’ve have had any exposure to physics, ABHOT is a relatively fun breeze which should rekindle some interest in wonderous entities like gravitational waves and particle colliders. I fondly recall a childhood where I’d exhaust my schoolmate Franky’s patience with latest developments at CERN–to what end are all of these atom smashers annihilating the unseen?
This is where ABHOT fails to become a transcendant work. For all the science, Hawking barely scrapes the philosophical surface. He rhapsodies briefly on the anthropic principle, but largely evades the important question and reason anyone bought this book. Is there a God? Do you see Him in those atom smashers and huge telescopes? A signature perhaps? Anything you can tell us about why we’re here, where we came from and where we’re going? Hawking flirts with the concept of a diety but only when its comfortable and it feels perfunctory and obligatory. Perhaps a new version would have some important updates from the author.

Papers I Read
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Proximity to Parental Symptom Onset and Amyloid-Beta Burden in Sporadic Alzheimer Disease. Villeneuve, et al. JAMA Neurol 2018.
This is a very sorry paper. The main finding is r^2=0.08, p=0.04. I don’t see how journals publish stuff like this. Like, I get that you wasted your government or whoever’s grant money and need to show SOMETHING. Write a nice “we’re sorry” card. Don’t publish. Or just say you found no correlation and publish in some crap journal. Shame!

FBXW7 regulates DISC1 stability via the ubiquitin-proteasome system. Yalla, et al. Mol Psych 2018,23:1278-1286.
This Pfizer (and academic collaborator) paper shows strong, capable science. DISC1 is an important protein and it is degraded by a specific E3 ligase, FBXW7. Unfortunately, FBXW7 has other important substrates. The authors think they can make an inhibitor that only inhibits the FBXW7-DISC1 interaction but I am very skeptical of that. When do we see that in medicine? Anyone? Anyway, as far as target discovery from immunoprecipitation all the way to crystallography, Yalla et al do a tremendous job here.

Two Phase 3 Trials of Bapineuzumab in Mild-to-Moderate Alzheimer’s Disease. Salloway, et al. NEJM 2014;370:322-33.
Nothing to see here. Just another important history lesson in drug development.

Biopharma & Investing
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A mega-price increase from a small company I had never heard of before: Aytu, who increased the price of their Ambien-containing nasal spray. This is actually a neat product, as some people have difficulty swallowing pills and it makes sense that a non-pill Ambien by the bedside may be easier to use. I once tried to buy a company (for $0 EV) called Transcept who made a ODT version of Ambien. That drug is now generic. If I worked at an HMO, I’d mandate people take that drug instead of the nasal spray. So, some price increases don’t work (or shouldn’t work). People who are on and are comfortable on this drug, however, are unlikely to be forced to switch. Maybe a higher copay (maybe much higher).

Beigene and Alnylam have similar valuations but extremely dissimilar prospects. Beigene is late-to-market in China for PD1 and extremely late to a crowded market in the US where they “share” economics with CELG. Their other drugs don’t target large markets. Alnylam has revolutionary technology which has proven successful in many clinical settings, with at least one drug that will sell well over $1 billion.

I’m starting to get worried about Bluebird. Wiping out your bone marrow and living in a hospital for 6 months may not be the cure for what ails you in the shadow of gene therapy for some illnesses and traditional modalities for others (sickle cell). But, BCMA!, you might say? Well, lots of companies have BCMA CART. The MM market is starting to worry me, too. We have lots of great drugs and we haven’t seen commercial success for CART yet. I’m starting to wonder about the upside here.

Some people want more from me on the subject of investing. I write this blog mostly for my teammates around the world who can study my notes and help my companies grow. I’m an unemployed passive investor, but if my philosophies and notes can be of use to someone, great. It’s free. I doubt I’ll give any structured theory of investing despite interest in a book on the subject. The grand unified theory for investing is still unclear to this observer, but I’ll share some explorations as they occur. I will probably write extensively on quantitative investing, value investing and other topics as time marches on.

One of my favorite questions in investing is how do you reconcile taxes in long-term market ‘expectations’? I, of course, believe that the expected median return for an individual global equity is actually negative. But if you are in the polyanna crowd, and you think for some insane reason that future stock performance will be 5% pa or something like that, how do you reconcile having to pay ~25% taxes (long-term rate) in the US? Does that make a 4% return a 3% return? How do you account for the asymmetry? And what about inflation, what is that really? In a world where the “price of goods and services” are irrelevant to a millionaire (any reasonable investor), shouldn’t the price of asset classes be your new inflation? After all, I’m not so worried about a tank of gas and a carton of milk. The prices of a Hamptons house and a La Ferrari are not in the current CPI basket, but your frame of reference is crucial to understanding inflation, in my opinion.

Anyway, if you believe, for whatever reason, that US stock markets going forward, measured by the S&P 500 index (implicit bias here, too), will average 5% per annum, what are you really getting? Well, you have to pay the 25% taxes, no matter what. I’m being generous as there are all kinds of hidden taxes, such as consumption tax, legal and accounting costs (which are, in essence, taxes). So that’s 3.75% net, but net of 2% inflation (whatever that is), you’re at 1.75% real returns. That’s including your massively foolish implicit bet that large-cap United States stocks have their best days ahead, as compared to say, China, India or any other country. You’d have to buy the Russell to avoid the large-cap bias, and perhaps hedge with international MNCs to avoid the US bias. If you could construct a basket of diverse market cap stocks, with their % of business in the US at perhaps 20%, you’d have a truly equity-like instrument. I think your performance net of inflation and taxes would be negative or zero. You might ask how this “system” could do anything but fall apart, in the long run. I’m not a perma-bear or anything like that. First, I don’t think expected return on equities is massively negative. Next, I think a large part of our financial system is constructed on a strange and amorphous foundation that still holds surprises for us. The stock market is ‘everything’ to so many, but real estate, private equity and other fields dwarf equities. Events in those markets impinge on stock performance such that sometimes its a good idea to pay $750 billion for $6 billion in annual (but growing!) cash flow and sometimes it isn’t. I’ll have more to say next time.

Papers I’ve Read
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A Phase 3 Trial of Semagacestat for Treatment of Alzheimer’s Disease. Doody et al. NEJM 2013 369;4:341-350.
This is maybe the third time I’ve read this paper from 5 years ago. It’s rare in medicine to get a hypothesis so wrong that the drug does a statistically significantly WORSE job than placebo. This gamma-secretase “inhibitor” worsens cognition and functioning. Some believe it is in fact, not a gamma-secretase inhibitor, but I don’t agree. Peripheral reduction of the putative causative agent of Alzheimer’s, amyloid-beta, was seen, but CSF (no mention of cortical) amyloid-beta was not. Brain disease is region specific (paracrine) and that makes treatment quite difficult. For instance, hippocampal amyloid-beta may be harder to target than perhaps more vascularized areas of the brain. So what explains -9 ADL for placebo and -13 for drug, a palpably worse effect? Two possibilities come to mind.
First, this drug is inhibiting some enzyme that is causing the effect seen. Whether that target is gamma-secretase or not is an entirely different question. If it is gamma secretase, two more sub-questions result. 1) Does regiospecific inhibition explain this phenomenon? We have APP for a reason. It is possible APP aids cognition or synpatic function or something in one cortical area and is problematic when it aggregates in another (hippocampus, amygdala). Oxytocin, serotonin and other neurotransmitters work this way. 2) The second major question is this drug is inhibiting gamma-secretase but that is not the primary causal effect. Many enzymes like GSAP are in this cascade and enzyme conformation often is a signal onto itself for feedback purposes. Stopping gamma-secretase, which ordinarly processes (cleaves) a precursor protein (a common theme in peptide signal biology, see endothelin, angiotensin), may prevent a key feedback signal telling some gene to stop making APP, resulting in paradoxically greater APP. We see reductions in AB, so one is tempted to reject this hypothesis, but AB alone may not be the whole story.
If semagacestat’s target is not gamma-secretase, what enzyme is it, and how could it serendipitously have such a profound impact on cognition? This seems highly unlikely, and we should use this opportunity to probe semagacestat further to understand AD biology. We see immune changes with human dosing, raising the possibility that AD results from immune aging, a hypothesis that was once also speculated for cancer. With no CSF AB or PET changes, one still has to question target engagement for sema. The dosing of 100mg vs 140mg is terribly awkward and hardly seen in medicine. That we see an increase in AB40 and AB42 reduction at 140mg is somewhat puzzling. Why not 200mg? What is DLT here and where is it coming from? Everyone seems to be pointing the finger at NOTCH inhibition but would that really explain increased dementia? If so, why not reverse this process? How about some CSF PK data?
Anyway, this one is an important mystery for current, future and prospective drug hunters to look back on and learn from. A pharmacological mystery.

Phase 3 Trials of Solanezumab for Mild-to-Moderate Alzheimer’s Disease. Doody, et al. NEJM 2014 370;4:311-321.
A lot of observers felt Lilly could have filed and received approval for sola on these barely-missed Phase IIIs. Certainly they stoke the idea that beta-amyloid intervention in AD should begin as early as possible and tantalize potential benefit with predictive diagnostics. That EXPEDITION 2 wasn’t repowered for only mild disease is unfortunate, they probably would have met a primary endpoint. Then, EXPEDITION 3 failed. So, just remember that subgroups are still subgroups and even with an a priori mechanism of action, there is a bit of luck involved in these trials, and trying to squeeze out a really small treatment effect in a new trial powered for that small effect is likely to backfire. Why develop a drug that is, at best, a modest therapy? The lack of binding fibrillar AB probably did this one in. A prodromal study is ongoing, I believe.

Personal
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Some people are interested in how sentencing works. Given that almost no one is a criminal defense attorney (a very tough job!), allow me to explain to the uninformed. In federal prison, there is no parole. “Good time” is roughly 15% of one’s sentence, assuming serious no violations (so far so good, on my end). However, the 15% is overstated, and actually works out to 13.8% or something like this. Some speculate that the entire 15% will be restored in a soon-to-come criminal justice reform. While I won’t hold my breath, you can look up and calculate the exact number of DAYS you would get on an 84 month sentence by statute. My attorneys and sentence consultant have done this, it’s around 12 months. As you may know, I was sentenced to 84 months, and as of two days ago, I have been in prison for 10 months, meaning I have 74 months to go. When you include “good time”, I would have 62 months left. We’ve only gotten started on calculating, however. Prisoners like me are able to do 10% of their sentence as “home confinement”, which would be 8.4 months. This option is not available to everyone, but for nonviolent crimes, it is available. It used to be 5% until very recently. Next, there is a program available to certain prisoners that reduces a sentence by 12 months. Finally, any half-way house time would overlap with home confinement time, but if greater than that time, would count. For instance, if halfway house of 12 months were assigned to a prisoner who had 8.4 months of home confinement time, that prisoner would simply get halfway house/home confinement of 12 months. So, 84 – 10 – 12 – 12 – 12 = 36. Of course, the final 12 could be as little as 8, and one of the 12s could be anywhere from 11.0 to 12.6. My lawyers and I are confident in those numbers, but the full range best case/worst case would be 35 to 40 months. So, I project I’m 37 months away from home at this time. I also have an appeal pending, don’t sleep on that 🙂 Anyone playing along at home is free to do their own calculations and comment on the site!

There’s a guy here who doesn’t know any Beatles songs. I think there are a few guys here. He wanted to know their most famous song. I said: “Yesterday, Hey Jude, Lucy in the Sky With Diamonds, err… Imagine? Yellow Submarine?”. Drew blanks. Did I miss one?

I think the left needs to talk about unity instead of resistance. I’d be willing to apologize to Lauren Duca for nagging and teasing her, apologize to Lena Dunham for offering to afford her private plane trip to Canada, and others. The right needs to reach across and stop the flame war, as fun as it is. People like Hannity, Carlson, Dinesh, Milo, any standard bearer for Republicans, should begin this process. If the left won’t agree to “lay down arms” and focus on strengthening our country instead of dividing us further, then their party will dwindle into irrelevance and implode in hatred (has it already happened?) But we shouldn’t follow that lead. Let’s find common ground and cease the incessant and overwrought narrative that everything left-of-center is malignant and everything right-of-center is righteous. My reasoning for this change of pace arises from witnessing the miserable sorrow of various pundits and commentators. Losing stinks, but cheer up. We can get through this together. We lose, too. Being happy is more important than having your life subsumed by complaining. You can be happy with Trump. I was happy with Obama. I was happy with Bush. I’m always happy because there are more important things than driving yourself (and others) crazy with politics. Some of us like politics, and are passionate about it, and that’s fine, too. But we can use a different, less inflammatory and flamboyant language to convey what we’re thinking. Sometimes the understated is far more effective than bombast.

Biopharma
—————
There are a lot of tau-focused drugs in the clinic: antibodies, antisense. Which will read out first? Hopefully better luck than amyloid. Probably still too late in the disease process to work, but who knows?

Zogenix has themselves a great drug. I wonder how it works. Maybe just 2B antagonism? Anyone know?

Let’s continue with our R&D productivity analysis. Last time we determined Pfizer would have been better off never investing in R&D, and instead contributing their R&D expense to a hypothetical investment fund earning 5% per year. How about Merck?

Genital inflammation undermines the effectiveness of tenofovir gel in preventing HIV acquisition in women. McKinnon et al. Nature Medicine 2018.
Lubricating and antiviral, not bad! Honestly, just take PreP pill. I guess I don’t understand global culture. How about a patch?

H3B-8800, an orally available small-molecule splicing modulator, induces lethality in spliceosome-mutant cancers. Seiler, et al. Nature Medicine 2018. This is really good drug discovery science but I fear really bad chemistry. Structure has ‘natural product’ written all over it and look at that chirality!

An Incomplete Prescription. President Trump’s Plan to Address high Drug Prices. Sarpatwari et al. JAMA 2018.
This is a joke. The easiest way to lower drug costs is to allow interchangable biosimilars. Old, off-patent biologics are our biggest drug cost. Not mentioned here. The part that really irks me is the authors’ foolish CPI statistics. Yes, drug costs have outpaced inflation. Why, is the question? Why are consumers demanding these goods so much that their prices are rising? Its not a producer-only phenomenon. It has happened since the 1960s. We care about health. Companies are producing great innovations. We have more disposable income than ever. None of this is bad. What perverse insanity this writing is. Not to mention 90% of medical costs come from two letters and one punctuation mark: Dr.

Flatland by Edwin Abbott – A Modern Vantage Point
————————————————————-
Flatland, though published in 1884, still has a voice that speaks to us today. A satire with a mathematical theme, Abbott not only indicts the backward Victorian-aristocrat thinking of his time but also wisely ruminates on higher dimensions. While Abbott foreshadowed the nearby Einstein (to a very small extent), he’d still be very happy to hear about Minkowski spaces and other manifolds where today’s minds contort themselves to understand higher spatial dimensions and fail. “We have no evidence to support the existence of a fourth spatial dimension, and if they do exist, they exist in a compressed and unobservable state”, a modern thinker might say. Not that Abbott was the first person to contemplate “4D” (Kant had him by a mile), but his narrative form is enchanting and illuminative for the simpler, 80-page readers among us.

What was Abbott saying from a psychosocial perspective? His perspective on heirarchy is timeless. Man’s attempt to find order in the world in relation to other men is futile and forgive me, circular. The sorrowful denizens of Flatland reasonably assign rank by the number of sides their person exhibits. The larger the number of sides, the more they approach the perfection ideal (that of a circle) and are accorded status as such. In today’s world, non-capitalist institutions such as politicians, government employees and the media resemble Flatlanders. Without the laissez-faires simplicity of financial order, the non-capitalists struggle to find order, and therefore, meaning. Capitalists have their own problems with meaning, which is an essay for another day. So, non-capitalists are Flatlanders, searching for a pecking order consisting mostly of who can make laws governing the capitalists, interpret and execute laws governing the capitalists, write stories about the capitalists, and sometimes simply and smugly, judge the capitalists. It’s good to govern (explicity in government and implicitly in the media) those you cannot compete with. This psychogical reordering is comfortable, like the pentagon who outranks the isosceles.

In Flatland, one irony is that large-sided polygons are so circle-like, but can never reach circlehood because they’re actually going backwards in the number of sides required: one. If anything, the lowly women, who are but “two-sided” (and often invisible) are closer to perfection than the 500-sided elder “circle”. So, too, it is with the non-capitalist group I described. What could be more frustrating right now than to be a lifelong politician/”civil servant”? To arrive in 2018 and realize you’ve accomplished nothing: President Trump just decided to become President and you are just some 200-sided shape trying to be 210-sided. The usurping of the aristocracy and the idiocy that created it in the first place is the point of Flatland. We don’t have an aristocracy in America, but we do have a strange edifice resembling some aristocratic properties. The government and media thrives on self-importance. Nothing makes journalists I confront angrier than when I tell them their stories don’t matter. No one reads them, no one believes them. You can call me “the most hated man in America”, but the reality is people cheer me and shake my hand everyday. I’ve gotten hundreds, maybe thousands of fan mail and two pieces of hate mail. Two! I’ve been in federal prison for ten months and have been treated like a hero for confronting media and government. If I’m hated, I’d like to see what loved looks like. Is that what Elizabeth Warren is? Nothing makes politicians/government officials angrier than when I make fun of them, often to their face. Don’t I know who they are? That they could put me in jail!?

The facade of the aristocracy’s power is what Flatland exposes. The facade is both the frustrated actions the edifice takes to self-perpetuate (laws, journalist output, the miasma of South Parkian smug filling our lungs) and its precious self-delusion, which must also not be shattered. Letting bubble-dwellers enjoy their setting is a reasonable way to handle their existence. Unfortunately, natural entropy occurs and the popping of safe spaces reminds the self-appointed enlightened that the path they chose is dim and foggy. The shape with the fewest sides, indeed, has the sharpest angles.

Personal
———-
The 13th is my favorite day of the month, as I was remanded on the 13th and it’s easy to count the months. I have about 3 years left exactly. That I’ll spend 5% of my life in isolated study isn’t pleasant but books like Frankel’s “Man’s Search For Meaning” puts things into perspective! Everyone said the biggest downside to jail is boredom. I am not bored… very, very far from it.

What’s the point of free speech? I’m censored from Twitter/Periscope, Twitch, Okcupid (!), Tinder (!!), and other websites. Why say anything if it’s not the consensus? CONSENUS KNOWS BEST.

Glossary
————
dyspnea. shortness of breath.
Heart Failure. A progressive and usually fatal cardiovascular illness where the heart cannot pump enough blood to meet the body’s demands.
Chronic Obstructure Pulmonary Disease (COPD). A progressive lung disease affecting millions of people where airways are obstructed.
spirometry. a breath test used to measure pulmonary function, resulting in important values such as FEV, FVC and lung volume.
cytokine (very important, very simple). A signaling protein, usually activates its cognate (matching) receptor (e.g. IL-6 binds IL-6R). Often used to send a pro-inflammatory or autoimmune signal. Target for many medicines including world’s best-selling drugs, the TNF antibodies.
interstitial (adj) / interstitium (n). the space between organs, sometimes called the “Third Space”.
alveoli (n., pl), alveola (n., si), alveolus (n., si), alveolar (adj). the basic, fundamental respiratory unit in the lung where oxygenation occurs.
pneumonia. inflammation of the alveoli

Biopharma
——————
–Does anyone think there is room for a lowish-priced antidepressant with a new MOA (not TRD)? I guess ALKS does. I gotta look at the data again but I really didn’t think that drug worked. I guess it’s true what they say, run 4 depression Phase IIIs to get two positive ones. Even JNJ’s data was underwhelming. GP/internist drugs are so scary now after so many flops, but look at Eliquis, doing amazingly well. So is 90s pharma over or not?

–On Acadia I wouldn’t be as worried about the safety as I would be on the commercial opportunities and intellectual property. Also a lot of the gain on this short has been realized.

–Sarepta and Madrigal are the two biotech stocks up the most this year. Congratulations to whoever owns those stocks. One fascinating thing is the success of some medtech stocks, including Align and Abiomed, which were favorites of mine (but mostly my old partner) in 2009-2011!

–Will be glancing at some stocks soon, including Alnylam, Fibrocell, Jazz, Endo and others. Was a bit focused on other matters.

Glossary
——————-
moscaism. Different genotypes present within a cell pool.
myc tag. Another small peptide tag used for protein identification and purification. Similar to the FLAG tags I used in my first experiments.
GFP. green fluorescent protein. A good reporter of gene/protein expression.
SNP (elementary concept, essential importance). single nucleotide polymorphism, a variation in a nucleotide at a specific position.
Hardy-Weinberg equilibrium. In genetics, an equation that predicts allele frequency. Often used to quality check sequencing in GWAS.
eQTL. expression quantitative trait loci – analysis of genetic loci that influence level of mRNA/protein expressed
Sanger sequencing. An older type of DNA sequencing relying on chain terminators. Still used in basic experiments, but not in NGS (next-generation sequencing).
cAMP. messenger molecule created from ATP by adenylate cyclase after a GPCR Gs receptor is activated.
parietal cortex.
MADRS. Montgomery-Asberg Depression Rating Scale. A commonly used scale for measuring major depression. >20 is depressed. Control patients usually have a rating of 0-1.
SSRI. Selective serotonin reuptake inhibitor. Class of drugs approved for depression including Zoloft (sertraline), Celexa (citalopram), Paxil (paroxetine), Lexapro (escitalopram) and others. All SSRIs are now generic.
Protein Kinase A.
phosphodiesterase. Also known as PDE, a class of enzymes that break phosphodiester bonds, including the one present in cAMP.
anoxia. lack of oxygen.
prefrontal cortex. area of the brain responsible for “executive function” including personality, complex behavior, decision making, etc. Mine is clearly highly developed.
cortical. refering to cortex areas of the brain, not the motor or sensory areas, but “higher” processing
subcortical. “below” cortex structures such as the amygdala, hypothalamus, etc.
bulbar dysfunction. neurological finding resulting in abnormal speech and swallowing. the bulbar structure is composed of the cerebellum, medulla and pons, with the medulla being the “bulb”.
bioavailability (elementary concept, critical importance). a PK measurement that compares the dose administered to the patient with the available drug level in the blood. It is a ratio sometimes indicated by the variable name F. The F of any IV administration of a drug is always 100%. Some drugs have very low bioavailability (10-20%) and pose a potential risk if blood levels are variable. Protein binding is an important consideration in contemplating drug availability in conjunction with bioavailability.
gene amplification. in an oncology context, a copy number change, often induced by selective/evolutionary pressure
splice variants. the product of alternative splicing (very important concept).
prometaphase. the phase in mitosis before metaphase where kinetochores form.
metaphase. the phase in mitosis before anaphase where chromosomes align prior to separation
cytokinesis. when the cytoplasm of a single cell divides into two.
monopolar spindles. a spindle defect.
kinetochore. a protein that forms the attachment point for the spindle to separate sister chromatids.
chromatid. the copy of a chromosome attached to its template by a centromere.
apraxia. the inability to complete a fine motor task.
GPCR. G-protein coupled receptor. 7-transmembrane family of receptors coupled to a G-protein. Very common pharmacological targets.

Personal
——————
I hate correcting the media. Some Vanity Fair reporter Emma Stefansky apparently said that my Wu-Tang album was no longer ‘mine’. That’s interesting since I pay for it to be stored and insured every month. Maybe someone can reach out to her and ask her who has it? Because I don’t know, I think I do. Maybe I’m wrong? Let me know.
The same thing applies to my finances. People know about 10% of the story. I’m wealther than I ever have been. Liquidity has always been a struggle for me. I don’t think I’ve ever been really liquid, basically ever. That’s just how it works with serial entrepreneurs who put everything they have into their companies. Elon Musk once said he couldn’t pay his rent. I think mere mortals don’t understand the concept of giving all you’ve got.
I’m sitting pretty though, as the IRS owes me a $4 million refund, I’m hopeful that the insane $7 million judgment gets reversed on appeal (which I’ve already paid most of), and I have about $22 million in uncashed options from my first company that I should probably cash in. It’s been difficult to do basic things like that since I was remanded for “hairjokegate” 2017. I guess I gotta find a notary here, they supposedly have one in the prison, but I’ve only been here for two months. Anyway, my private holdings are growing more valuable by the day, so I find it funny reading all the misinformed stuff about me.
One person told me “eh, don’t correct aynone, it will be even funnier when you buy a sports team and people will say ‘what a comeback'”. But, there’s nothing to “come back” from. Jail is adult time out. I haven’t learned anything profound from this experience, other than doing what most prisoners do, which is to stew and grow more resentful of our overreaching and corrupt law enforcement. I’m innocent and was narrowly convicted with the assistance of witness coercion, the government obtaining illegal evidence and all kinds of other government tricks. They certainly prosecute the person, not the crime. Lucky Luciano, Al Capone, you name it. A bad guy is a bad guy, doesn’t matter what they did. They’re trying to do it to our President as we speak. What law did he violate, so that we can get vengence for the political policies we don’t like? Shame on the FBI–it should be shut down. [End Count of Monte Crisco rant.]

Biopharma
——————Acadia. I still don’t think this drug will ever sell too much. There are a few D2 sparing 5-HT2a antagonists (nothing as pure as pimavanserin, given), but the company’s spending is a bit insane. The drug is probably great for PDP given the levodopa interference at the dopamine receptor, but what good is the drug for the other illnesses when you can use Risperdal, Abilify, Seroquel, etc. Re spending, I understand that one needs to invest in a brand, and it will stop at some point, but this is quite dramatic cash use. I am skeptical of the intellectual property of pima, so I expect a generic sooner than others.

Continuing our Pfizer (Merck next) R&D productivity analysis, what is fascinating is almost all of Pfizer’s drugs were discovered by other companies. I suppose it is not too surprising given the mega-mergers that have occured. Still, the idea that Pfizer has only created 11 drugs in the last 30 years despite spending >$100 billion on R&D fascinates me.

I assumed net margins on pharmaceutical products are 50% (well above what they really are but around what they are on a steady-state well-managed level). I assumed 50% of R&D is spent on discovering or running clinical trials for in-house projects (as opposed to clinical trials for acquired products). At a 3% discount rate, PFE made 32B for shareholders from 1991 to 2017 (16 years) investing in R&D. All of the profit was from 1992 to 2006, indicating very roductive R&D in the 1990s, creating monsters like Norvasc, Viagra and Zoloft. Net income of this “inHouseR&DOnlyCo” reached as much as $2 billion in some years. Net income turned negative afterwards, ranging from breakeven to negative 1 billion per annum since 2006.

If, instead of doing R&D, Pfizer invested the R&D cost (50% of reported cost) in a fund returning 5% after-tax, it would have generated 124B in value as opposed to the 32B NPV. I have never seen an analysis like this done (it has taken me the better part of 3 days).

Personal
————-
I’ve been having a recurring dream about being able to go back in time and see the future and live the past simultaneously. I’m working at a hedge fund and I somehow know the future years in advance. I know that Facebook will get started in 2004. I know that Google is a great buy at or before the IPO. I know what drugs will work and what won’t (although I know that today). I knew the market will crash in 2000-2002 and recover in 2003. I guess this is what insider traders feels like?

Papers I’ve Read Recently
——————————-Idiopathic Pulmonary Fibrosis. Lederer & Martinez. NEJM 2018:378;19.
This is the kind of review article I like to see in the NEJM, especially as it covers emerging therapeutic options. Bravo!

Biopharma & Investing
—————-
In demonstrating PFE and MRK to an inmate here, I was reminded of the poor R&D productivity of big pharma. I’ll do a little more of an in-depth analysis but if you take the aggregate R&D spend of these two “industry leaders” and evaluate what projects ended up being successful, what are we left with? Only compounds definitely from within count. Buying Schering who bought Organon and lucking out on Keytruda doesn’t count. I’ll try and trace back the origins of each compound.

–Very glad to see the WSJ take Greenlight down a notch. There’s a joke in there about me. Well, I guess the jokes on Einhorn. He passed on my company and I project that is up about 4x. Meanwhile his Greenlight fund is… uh… not doing so well, apparently. I’m far better off than he was at my age, and at the rate he is losing money and I’m making it, I’ll be wealthier than him soon even without the 15 years he has on me. Keep shorting NFLX and AMZN bro, you gotta be right someday.

Book Review
—————-
The Dhandho Investor – Monish Pabrai

This is one of the worst books I’ve ever read. Most investing books suck, and Pabrai breaks new ground in the arcane field of suction engineering. Pabrai is what I would call a weak-form Buffett clone, and appropriately comes off as embarassingly clueless. The only property of this work worse than its content, which lacks one original thought, is Pabrai’s putrid writing style. I lost count at how many times he printed his meaningless platitude “heads I win, tails I don’t lose much”. Pabrai believes he’s doing the world a favor by writing, but I suggest he finds a new hobby. As if the secrets of wealth are contained in 180 pages of regurgitated “value investing basics”, Pabrai’s arrogance is intolerable. He doesn’t mention that, like any investment strategy, value investing can become wildly overcrowded and ineffective. Why are all the value hedge funds doing so poorly? I guess they haven’t picked up this classic.

Contradicting himself repeatedly, Pabrai screws up basic calculations, doesn’t explain (frequently being wrong) key inputs to important formulas. He stresses simplicity, but misses the point that investing, in fact, is anything but simple. Take Buffett. I consider myself a Buffettologist and have learned a lot about this legendary investor. From what I can tell, Mr. Buffett and Berkshire Hathaway have been a leveraged, long-only beta bet on American equities. It has worked well. The false conclusion drawn by Pabrai and his sorry acolytes is that we should be like Buffett. America has changed. We are a very leveraged country and much larger, among other differences. I have no idea if the great bull run of the 60s-present day will continue. Neither does Pabrai. The US may be the next Japan or Russia (two leading countries in the 70s), or worse. The question of ‘why is it so easy?’ apparently never enters Pabrai’s mind. The answer is because it isn’t. Nowhere does Pabrai suggest holding cash in a portfolio or entering into more complex transactions.

Even in relative bright spots, like a fairly pathetic tour of his successful investments, Pabrai’s level of ignorance is astonishing. His funeral home example excludes the company’s gigantic debt load from his calculations, happily allowing him to pronounce his purchase of the company’s stock at 3x cash flow. Yes, I too can ask Bloomberg to print me out a list of enormously overvalued companies ‘trading at low P/Es’. I was perhaps this ignorant when I was 17 years old, in my first year on Wall Street. Some examples, like his Level Three convertible bond “analysis” are superficially fun, but show the Buffett sycophant syndrome. He buys these bonds because Buffett buys the bonds. Okie, dokie. Pabrai’s application of the Kelly criterion is also laughable, often humorously suggesting to put 90% of one’s portfolio in an equity.

I hate to criticize other investors or beat my chest and imply “I’m richer than you” or “I’m smarter than you”. But I must implore you to ignore this book, or read it with an eye to correcting it. I’m not sure who sent it to me, but you hurt me. Why are you hurting me? One should read about great investors like Buffett, but try to abstract the governing dynamics of their actions. “Buffett started an insurance company. So should I!” “Buffett bought a lot of American Express during their crisis, I should do something like that!”. These are all unoriginal and overly simplistic thoughts that will teach you nothing and lead you astray. Investing actions are a manifestation of your investing theory. If you discover and understand, and then extend theory, you can create actions that aren’t simple acts of mimicry.

There are exceedingly important questions the advanced investor has to ask: are there times when I can discount future cash flow at very low (close to zero) rates? Is investing a “zero-sum game”? What is the relationship between arbitrage and crime/ethics? What can we infer from liquidity? Pabrai reminds me of the old SNL skit “Deep Thoughts”, the modern day equivalent of the philosoraptor. Except, even those constructs grope for a further truth and a refinement of technique. Not Pabrai, he’s got Dhandho.

Papers I read today and yesterday
——————————————

The protocadherin 17 gene affects cognition, personality, amygdala structure and function, synapse development and risk of major mood disorders. Chang et al. Molecular Psychiatry 2018,23:400-412.
Interesting paper on a new target. First thing I ask myself when I read something like this is, how many AA is PCDH17 and is there a crystal structure?

The Lymph Node and the Metastasis. Tjan-Heijnen & Viale. NEJM 378;21.
Another “Clinical Implications of Basic Research”. Oh boy. Here we debate the irrelevant question of how tumors seed metastases. I don’t think it matters.

Correction of a splicing defect in a mouse model of congenital muscular dystrophy type 1A using a homology-directed-repair-independent mechanism. Kemaladewi et al. Nature Medicine 2017.
I reread this paper. It actually is a bit of a breakthrough, delivering CRISPR through AAV9 and selecting just the right PAM to excise/correct/create just the right donor splice-spite mutation in post-mitotic tissue. The animal data is impressive and augurs well for humans. I’m a little wary of the immunogenicity of the humorous delivery of gene editing through a viral vector. I also have questions about what drives expression from the episomes, but you can’t argue with the data!

Glossary
———-synapse. The gap between neurons where chemical or electrical messages are sent. Understand the difference between presynapse and postsynapse.amygdala. Bilateral brain structure in the temporal lobe responsible for a variety of functions including memory and emotion (not just rage as we’re taught in school). Close in proximity to the hippocampus.hippocampus. Bilateral brain structure in the temporal lobe responsible for memory consolidation among ther functions.temporal lobe. Major area of the brain responsible for interpreting sensory input and many other things.dendrite. branched extensions of neurons that receive impulses/signals.
dendritic spine density. the arborization of dendrites is thought to be important for various illnesses. the more dense the better.GWAS. genome-wide association studies. The study of entire genome (or exome) and its correlation to some phenotype. Beware multiplicity statistical errors, which are frequent in GWAS.NHEJ. Non-homologous end joining. Contrasted with HDR, NHEJ allows for double strand break correction without a template. More error prone than HDR.Protospacer-adjacent motif. A target region for Cas9 nuclease activity.Single guide RNA. Guides CRISPR to nuclease site.spliceosome. Cellular apparatus that removes introns from RNA.donor splice site. 5′ site of intron to be spliced out.post-mitotic cell. Cell that will no longer undergo mitosis. E.g. neurons.hemagglutinin-tag. Similar to other tags like His6, FLAG, SUMO etc., tag proteins with short amino acid sequence to assist purification and identification. Used FLAG for my first proteins until I realized it really is a research tool. I believe there is one FDA approved drug with the tag intact, however (LOL!).
syngeneic model. An animal model using a tumor allograft from the same species/background to ensure immune competence.